In this paper I define an evolutionary stability criterion for learning rules. Using Monte Carlo simulations, I then apply this criterion to a class of learning rules that can be represented by Camerer and Ho's (1999) model of learning. This class contains perturbed versions of reinforcement and...

In this paper, I analyze stochastic adaptation in finite n-player games played by heterogeneous populations of myopic best repliers, better repliers and imitators. In each period, one individual from each of n populations, one for each player role, is drawn to play and chooses a pure strategy...

This paper investigates why subjects in laboratory experiments on quantity precommitment games consistently choose capacities above the Cournot level - the subgame-perfect equilibrium. We argue that this puzzling regularity may be attributed to players' perceptions of their opponents' skill or...

Micro data from a dental insurance natural experiment is used to analyze why agents opt out of insurance. The purpose is to relate the dropout decision to new information on risk, acquired by the policy holder and the insurer. The results show that agents tend to leave the insurance when...

Behavioral economics provides several motivations for the common observation that agents appear somewhat unwilling to deviate from recent choices: salience, inertia, the formation of habits, the use of rules of thumb, or the locking in on certain modes of behavior due to learning by doing. This...